Abnormality Detection in Endoscopic Images Using Color Segmentation and Curvature Computation

In this paper, a method for detecting possible presence of abnormality in the endoscopic images of lower esophagus is presented. The pre-processed endoscopic color images are segmented in the HSI color space. The zero-crossing method of edge detection is applied on the binary image corresponding to the segmented image. For the large contours, the Gaussian smoothing is performed for eliminating the noise in the curve. The curvature for each point of the curve is computed considering the support region of each point. The possible presence of abnormality is identified, when curvature of the contour segment between two zero crossing has the opposite curvature signs to those of such neighboring contour segments on the same edge contours. The experimental results for the proposed method show successful abnormality detection in the test images.